Human visual system compensates for different lighting conditions and color temperatures so that white objects can be perceived as white in most of the situations. AWB algorithms that are used in digital cameras try to do the same things for raw images that are captured by digital camera sensors. That is, AWB adjusts the gains of different color components (e.g. R, G and B) with respect to each other in order to present white objects as white, despite the color temperature differences of the image scenes or different sensitivities of the color components.
One of the existing methods of the AWB is to calculate averages for all of color components, and then apply an appropriate gain for each color component so that those averages become equal for each other. These types of methods are often called “grey world” AWB algorithms.